@langgraph-js/sdk

The missing UI SDK for LangGraph - seamlessly integrate your AI agents with frontend interfaces

Why @langgraph-js/sdk?

Building AI agent applications is complex, especially when you need to bridge the gap between LangGraph agents and interactive user interfaces. This SDK solves the critical challenges of frontend integration:

• Provides a complete UI integration layer - no more complex custom code to handle tools, streaming, and state management
• Simplifies human-in-the-loop interactions - easily incorporate user feedback within agent workflows
• Handles edge cases automatically - interruptions, errors, token management and more
• Offers a rich set of UI components - ready-to-use elements to display agent interactions

DOCS

Installation

# Using npm
npm install @langgraph-js/sdk

# Using yarn
yarn add @langgraph-js/sdk

# Using pnpm
pnpm add @langgraph-js/sdk

Key Features

Generative UI

• ✅ Custom Tool Messages
• ✅ Token Counter
• ✅ Stop Graph Progress
• ✅ Interrupt Handling
• ✅ Error Handling
• ✅ Spend Time Tracking
• ✅ Time Persistence

Frontend Actions

• ✅ Definition of Union Tools
• ✅ Frontend Functions As Tools
• ✅ Human-in-the-Loop Interaction
• ✅ Interrupt Mode

Authorization

• ✅ Cookie-Based Authentication
• ✅ Custom Token Authentication

Persistence

• ✅ Read History from LangGraph

Legacy Mode

Legacy mode is designed to be compatible with environments that don't support AsyncGeneratorFunction (such as WeChat Mini Programs). In these environments, standard async iterators may not work properly.

Legacy Mode Example

import { TestLangGraphChat, createChatStore, createLowerJSClient } from "@langgraph-js/sdk";

const client = await createLowerJSClient({
    apiUrl: "http://localhost:8123",
    defaultHeaders: {
        Authorization: "Bearer 123",
    },
});

createChatStore(
    "graph",
    {
        defaultHeaders: {
            Authorization: "Bearer 123",
        },
        client,
        legacyMode: true,
    },
    {}
);

Advanced Usage

Creating a Chat Store

You can easily create a reactive store for your LangGraph client:

import { createChatStore } from "@langgraph-js/sdk";

export const globalChatStore = createChatStore(
    "agent",
    {
        // Custom LangGraph backend interaction
        apiUrl: "http://localhost:8123",
        // Custom headers for authentication
        defaultHeaders: JSON.parse(localStorage.getItem("code") || "{}"),
        callerOptions: {
            // Example for including cookies
            // fetch(url: string, options: RequestInit) {
            //     options.credentials = "include";
            //     return fetch(url, options);
            // },
        },
    },
    {
        onInit(client) {
            client.tools.bindTools([]);
        },
    }
);

React Integration

First, install the nanostores React integration:

pnpm i @nanostores/react

Then use the ChatProvider in your components:

import { ChatProvider, useChat } from "@langgraph-js/sdk/react";

Use it in your components:

export const MyChat = () => {
    return (
        <ChatProvider
            defaultAgent="agent"
            apiUrl="http://localhost:8123"
            defaultHeaders={{}}
            withCredentials={false}
            showHistory={true}
            showGraph={false}
            onInitError={(error, currentAgent) => {
                console.error(`Failed to initialize ${currentAgent}:`, error);
                // Handle initialization error
            }}
        >
            <ChatComp />
        </ChatProvider>
    );
};

function ChatComp() {
    const chat = useChat();
    // Use chat store methods and state here
}

Vue Integration

First, install the nanostores Vue integration:

pnpm i @nanostores/vue

Then use the ChatProvider in your components:

import { ChatProvider, useChat, useChatProvider } from "@langgraph-js/sdk/vue";

Option 1: Using ChatProvider Component

Use it in your components:

<template>
    <ChatProvider
        :default-agent="'agent'"
        :api-url="'http://localhost:8123'"
        :default-headers="{}"
        :with-credentials="false"
        :show-history="true"
        :show-graph="false"
        :on-init-error="
            (error, currentAgent) => {
                console.error(`Failed to initialize ${currentAgent}:`, error);
                // Handle initialization error
            }
        "
    >
        <ChatComp />
    </ChatProvider>
</template>

<script setup lang="ts">
import { ChatProvider } from "@langgraph-js/sdk/vue";

function ChatComp() {
    const chat = useChat();
    // Use chat store methods and state here
}
</script>

Option 2: Using useChatProvider Hook Directly

For more flexibility, you can use the hook directly in your setup:

<script setup lang="ts">
import { useChatProvider } from "@langgraph-js/sdk/vue";

const props = {
    defaultAgent: "agent",
    apiUrl: "http://localhost:8123",
    defaultHeaders: {},
    withCredentials: false,
    showHistory: true,
    showGraph: false,
    onInitError: (error: any, currentAgent: string) => {
        console.error(`Failed to initialize ${currentAgent}:`, error);
        // Handle initialization error
    },
};

const { unionStore } = useChatProvider(props);
// Use unionStore methods and state here
</script>

<template>
    <ChatComp />
</template>

Documentation

For complete documentation, visit our official docs.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the Apache-2.0 License.